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Research Assistant in Bayesian Deep Learning

Applications for this vacancy closed on 30 October 2019 at 12:00PM
The Oxford Applied and Theoretical Machine Learning group at the Department of
Computer Science has a new opening for a Researcher in Bayesian deep learning,
working together with Professor Yarin Gal, in an industrial partnership with
Accenture. Conducting original research in this area, you will develop
fundamental tools at the core of Bayesian deep learning in the context of
real-world AI problems.



The aim of this project is to develop principled but practical safe AI methods
in Bayesian deep learning which are practical, i.e. could be used in real
systems. This requires coping with challenges such as intractable
probabilistic inference and robustness. The focus of the project is on methods
for i) Bayesian machine learning, and ii) deep learning. The project thus
requires familiarity with the fields above, and experience in at least one of
the fields. The project will involve both theoretical work as well as
empirical analysis on challenging tasks.



The primary selection criteria are an MSc degree in computer science or
related discipline, together with related experience, a documented track
record of the ability to conduct and complete research projects, as witnessed
by published work in machine learning on the specific topics of Bayesian deep
learning, and strong mathematical skills in probability and statistics. Good
knowledge of the current state-of-the-art in safe AI and Bayesian deep
learning, and experience managing projects is highly desirable.



The closing date for applications is 12.00 noon on Wednesday 30 October 2019.



Our staff and students come from all over the world and we proudly promote a
friendly and inclusive culture. Diversity is positively encouraged, through
diversity groups and champions, for example www.cs.ox.ac.uk/aboutus/women-cs-
oxford/index.html, as well as a number of family-friendly policies, such as
the right to apply for flexible working and support for staff returning from
periods of extended absence, for example maternity leave.

dc:spatial
Department of Computer Science, Wolfson Building, Parks Road, Oxford.
Subject
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oo:formalOrganization
oo:organizationPart
vacancy:applicationClosingDate
2019-10-30 12:00:00+00:00
vacancy:applicationOpeningDate
2019-10-16 09:00:00+01:00
vacancy:furtherParticulars
vacancy:internalApplicationsOnly
False
vacancy:salary
type
comment
The Oxford Applied and Theoretical Machine Learning group at the Department of
Computer Science has a new opening for a Researcher in Bayesian deep learning,
working together with Professor Yarin Gal, in an industrial partnership with
Accenture. Conducting original research in this area, you will develop
fundamental tools at the core of Bayesian deep learning in the context of
real-world AI problems.



The aim of this project is to develop principled but practical safe AI methods
in Bayesian deep learning which are practical, i.e. could be used in real
systems. This requires coping with challenges such as intractable
probabilistic inference ...

The Oxford Applied and Theoretical Machine Learning group at the Department of Computer Science has a new opening for a Researcher in Bayesian deep learning, working together with Professor Yarin Gal, in an industrial partnership with Accenture. Conducting original research in this area, you will develop fundamental tools at the core of Bayesian deep learning in the context of real-world AI problems.


The aim of this project is to develop principled but practical safe AI methods in Bayesian deep learning which are practical, i.e. could be used in real systems. This requires coping with challenges such as intractable probabilistic inference ...

label
Research Assistant in Bayesian Deep Learning
notation
143468
based near
page